## Loading required package: ggplot2
## Loading required package: cowplot
##
## ********************************************************
## Note: As of version 1.0.0, cowplot does not change the
## default ggplot2 theme anymore. To recover the previous
## behavior, execute:
## theme_set(theme_cowplot())
## ********************************************************
## Loading required package: Matrix
## Registered S3 method overwritten by 'R.oo':
## method from
## throw.default R.methodsS3
##
## Attaching package: 'tidyr'
## The following objects are masked from 'package:Matrix':
##
## expand, pack, unpack
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
##
## Attaching package: 'magrittr'
## The following object is masked from 'package:tidyr':
##
## extract
Look at changes in gene expression of lola target genes
Project: Promoter Opening
Author: Vivek
Generated: Mon Jan 24 2022, 06:15 AM
## Scaling data matrix
## Scaling data matrix
## Scaling data matrix
## Scaling data matrix
## Scaling data matrix
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in dtw(x = align.1, y = align.2, keep.internals = TRUE, dist.method
## = metric.use): Argument dist.method does not usually make a difference with
## single-variate timeseries
## Warning in as_grob.default(plot): Cannot convert object of class environment
## into a grob.
## Warning in as_grob.default(plot): Cannot convert object of class NULL into a
## grob.
For reproducibility, this analysis was performed with the following R/Bioconductor session:
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] RColorBrewer_1.1-2 magrittr_1.5 dplyr_0.8.3 tidyr_1.0.0
[5] Seurat_2.3.1 Matrix_1.2-17 cowplot_1.0.0 ggplot2_3.2.1
[9] pander_0.6.3
loaded via a namespace (and not attached):
[1] diffusionMap_1.2.0 Rtsne_0.15 VGAM_1.1-3
[4] colorspace_1.4-1 ellipsis_0.2.0.1 ggridges_0.5.1
[7] class_7.3-15 modeltools_0.2-23 mclust_5.4.6
[10] htmlTable_1.13.1 base64enc_0.1-3 proxy_0.4-24
[13] rstudioapi_0.10 npsurv_0.4-0 flexmix_2.3-17
[16] prodlim_2019.11.13 lubridate_1.7.9 ranger_0.12.1
[19] codetools_0.2-16 splines_3.6.1 R.methodsS3_1.7.1
[22] lsei_1.2-0 robustbase_0.93-6 knitr_1.24
[25] zeallot_0.1.0 tclust_1.4-2 jsonlite_1.6
[28] Formula_1.2-3 Cairo_1.5-10 pROC_1.16.2
[31] caret_6.0-86 ica_1.0-2 cluster_2.1.0
[34] kernlab_0.9-29 png_0.1-7 R.oo_1.22.0
[37] compiler_3.6.1 backports_1.1.4 assertthat_0.2.1
[40] lazyeval_0.2.2 lars_1.2 acepack_1.4.1
[43] htmltools_0.3.6 tools_3.6.1 igraph_1.2.4.1
[46] gtable_0.3.0 glue_1.3.1 RANN_2.6.1
[49] reshape2_1.4.3 Rcpp_1.0.5 jquerylib_0.1.4
[52] vctrs_0.2.0 gdata_2.18.0 ape_5.3
[55] nlme_3.1-141 iterators_1.0.12 fpc_2.2-8
[58] lmtest_0.9-37 gbRd_0.4-11 timeDate_3043.102
[61] xfun_0.29 gower_0.2.2 stringr_1.4.0
[64] lifecycle_0.1.0 irlba_2.3.3 gtools_3.8.1
[67] DEoptimR_1.0-8 zoo_1.8-6 MASS_7.3-51.4
[70] scales_1.0.0 ipred_0.9-9 doSNOW_1.0.18
[73] parallel_3.6.1 reticulate_1.13 pbapply_1.4-2
[76] gridExtra_2.3 segmented_1.2-0 rpart_4.1-15
[79] latticeExtra_0.6-28 stringi_1.4.3 foreach_1.5.0
[82] checkmate_1.9.4 caTools_1.17.1.2 bibtex_0.4.2
[85] lava_1.6.8 dtw_1.22-3 Rdpack_0.11-0
[88] SDMTools_1.1-221.1 rlang_0.4.0 pkgconfig_2.0.2
[91] prabclus_2.3-2 bitops_1.0-6 evaluate_0.14
[94] lattice_0.20-38 ROCR_1.0-7 purrr_0.3.2
[97] labeling_0.3 recipes_0.1.13 htmlwidgets_1.3
[100] tidyselect_0.2.5 plyr_1.8.4 R6_2.4.0
[103] snow_0.4-3 gplots_3.0.1.1 generics_0.0.2
[106] Hmisc_4.2-0 pillar_1.4.2 foreign_0.8-72
[109] withr_2.1.2 mixtools_1.2.0 fitdistrplus_1.0-14
[112] survival_2.44-1.1 scatterplot3d_0.3-41 nnet_7.3-12
[115] tsne_0.1-3 tibble_2.1.3 crayon_1.3.4
[118] KernSmooth_2.23-15 rmarkdown_2.11 grid_3.6.1
[121] data.table_1.12.2 FNN_1.1.3 ModelMetrics_1.2.2.2
[124] metap_1.1 digest_0.6.20 diptest_0.75-7
[127] R.utils_2.9.0 stats4_3.6.1 munsell_0.5.0